ASKII CLI ( •_•)>⌐■-■ (⌐■_■)

AI code assistant for your terminal. Powered by Ollama, LM Studio, OpenAI, Anthropic, opencode Go, or ASKII Cloud.

Install

npm install -g askii-cli

Or run without installing:

npx askii-cli <command>

Interactive Mode

Run askii with no arguments to start an interactive REPL session:

askii
askii --platform anthropic   # start with a specific platform

ASKII ( •_•)>⌐■-■ (⌐■_■)  — interactive mode

  Platform : ollama (gemma4:e4b)
  Workspace: /your/project
  Wiki     : off

Type a message to chat, /help for commands, /exit to quit.

> what does a closure do in JavaScript?

ASKII: A closure is a function that retains access to variables
from its enclosing scope even after that scope has finished...

> can you give me an example?

ASKII: Sure! Here's a classic counter example...

> /platform anthropic
Platform → anthropic (claude-sonnet-4-6)

> /do add a .gitignore for a Node.js project
[Round 1/5]
...

> /exit
Bye! ( •_•)>⌐■-■ (⌐■_■)

Bare text input maintains a persistent chat history across turns — follow-up questions remember the full conversation. Use /clear to start fresh.

REPL slash-commands

| Command | Description | | ----------------------------- | ---------------------------------------------------------------------------- | | /help | Show all available commands | | /ask <question> | Explicit ask (same as bare text) | | /do <task> [flags] | Run the Do agent (--max-rounds N, --yes) | | /generate <type> <base> | Generate a file (test / doc / json) — agentic, can search & ask | | /commit | Generate a commit message from staged/working-tree diff | | /note <subcommand> | Notes / tasks / reminders (add, list, search, done, delete, due) | | /edit --file <path> <instr> | Edit a file in place | | /explain <text> | Explain a line of code | | /wiki-reload | Rebuild the docs wiki index | | /platform <name> | Switch platform for the session (also updates default model) | | /model <name> | Switch model for the session | | /config | Show current session config (keys redacted) | | /clear | Clear chat history and start a fresh conversation | | /exit, /quit | Exit interactive mode |

Tab-complete any / command by pressing Tab. Up/down arrows cycle through input history.

Config overrides — bare -- flags at the prompt update session config without restarting:

> --platform openai --model gpt-4-turbo
> --max-rounds 10
> --mode helpful

Ctrl+C during /do or /control cancels only that agent and returns to the > prompt. Ctrl+C at the idle prompt exits.

Commands

ask — Ask a question about code

Pipe code via stdin or use --code:

bash

cat myfile.ts | askii ask "what does this do?"
askii ask --code "const x = 1 + 1" "is this correct?"

PowerShell

Get-Content myfile.ts | askii ask "what does this do?"
askii ask --code "const x = 1 + 1" "is this correct?"

edit — Edit code

Returns the modified code to stdout (pipe-friendly):

bash

cat myfile.ts | askii edit "add error handling" > myfile-edited.ts
cat myfile.ts | askii edit "convert to async/await"

PowerShell

Get-Content myfile.ts | askii edit "add error handling" | Set-Content myfile-edited.ts
Get-Content myfile.ts | askii edit "convert to async/await"

explain — Explain a line of code

bash

askii explain "arr.reduce((a, b) => a + b, 0)"
cat myfile.ts | askii explain

PowerShell

askii explain "arr.reduce((a, b) => a + b, 0)"
Get-Content myfile.ts | askii explain

do — Agentic task runner

Prints the working directory's top-level file listing, then runs an agent loop that creates, modifies, renames, deletes, views, and lists files until the task is done or --max-rounds is reached.

bash

askii do "create a Jest test file for src/utils.ts"
askii do "rename all .js files to .ts in the src folder"
askii do "add a .gitignore for a Node.js project"
askii do --yes "scaffold a README for this project"   # auto-confirm all
askii do --dir ./my-project "refactor index.ts"

PowerShell

askii do "create a Jest test file for src/utils.ts"
askii do "rename all .js files to .ts in the src folder"
askii do "add a .gitignore for a Node.js project"
askii do --yes "scaffold a README for this project"   # auto-confirm all
askii do --dir .\my-project "refactor index.ts"

The agent can use the following actions each round:

| Action | Description | Requires confirmation | | ------------- | ----------------------------------------------------------- | --------------------- | | list | List files in a folder ([file] / [folder] labels) | No | | view | Read a file's contents | No | | search | Grep workspace files for a pattern | No | | wiki_search | BM25 search over indexed .md docs (requires --use-wiki) | No | | create | Create a new file | Yes | | modify | Replace text in an existing file | Yes | | rename | Rename or move a file | Yes | | delete | Delete a file | Yes | | run | Run a shell command | Yes (always) |

The loop continues after every round — not only after reads — until the AI returns [] or the round limit is hit.

generate — Agentic file generator

Picks a file type (Test / Doc / Json) and a base name, then runs a Do-style loop that searches the workspace, asks clarifying questions when needed, and creates the generated file. The agent decides the full path and extension based on workspace conventions.

bash

askii generate test utils --file src/utils.ts --instruction "use Jest"
askii generate doc api --dir ./my-project
askii generate json schema --file package.json
askii generate test utils --yes   # auto-confirm (no clarifications prompted)

PowerShell

askii generate test utils --file src/utils.ts --instruction "use Jest"
askii generate doc api --dir .\my-project
askii generate json schema --file package.json
askii generate test utils --yes

Each round the agent can use:

| Action | Description | Prompts you? | | ------------- | --------------------------------------------------------------------- | ------------ | | list | List files in a folder ([file] / [folder] labels) | No | | view | Read a file's contents | No | | search | Grep workspace files for a pattern | No | | wiki_search | BM25 search over indexed .md docs (requires --use-wiki) | No | | clarify | Ask you a clarifying question (type your answer at the prompt) | Yes | | create | Create the generated file (written directly; Undo offered at the end) | No |

Optional flags:

• --file <path> — read this file as context (acts as the "current tab")
• --instruction <text> — extra instructions for the generator
• --dir <path> — working directory (default: cwd)
• --yes — auto-confirm (skips clarification prompts)

control — Screen control agent

Takes a screenshot, sends it to the AI, and executes the returned mouse/keyboard action. Repeats until the AI returns DONE or --max-rounds is reached. Requires a vision-capable model (e.g. llava, moondream2).

Linux: requires xdotool for mouse/keyboard control (sudo apt install xdotool or equivalent).

bash

askii control --ollama-model llava "open Notepad and type hello world"
askii control --yes --ollama-model llava "click the search bar and search for cats"
askii control --max-rounds 10 --ollama-model llava "fill in the login form"
askii control -p lmstudio --lmstudio-model llava-1.5 "open the browser"

PowerShell

askii control --ollama-model llava "open Notepad and type hello world"
askii control --yes --ollama-model llava "click the search bar and search for cats"
askii control --max-rounds 10 --ollama-model llava "fill in the login form"
askii control -p lmstudio --lmstudio-model llava-1.5 "open the browser"

Each round the AI can return one of:

• mouse_move — move the cursor to (x, y)
• mouse_left_click — left-click at (x, y)
• mouse_right_click — right-click at (x, y)
• keyboard_input — type a string
• DONE — task complete, stop the loop

Without --yes, each proposed action is shown with its reasoning and requires y confirmation before executing.

wiki-reload — Index wiki documentation

Walks all .md files under --wiki-path, splits them into sections by heading, builds a MiniSearch BM25 index, and saves it as .askii-wiki-index.json inside the wiki folder. Run this once after pointing --wiki-path at your docs, and again whenever the docs change.

bash

askii wiki-reload --wiki-path ./docs
askii wiki-reload --wiki-path /home/user/my-project/docs

PowerShell

askii wiki-reload --wiki-path .\docs
askii wiki-reload --wiki-path C:\my-project\docs

After indexing, pass --wiki-path and --use-wiki to any ask, edit, or do command to inject the top matching documentation chunks as context:

bash

askii ask --wiki-path ./docs --use-wiki "how do I configure the database?"
cat src/db.ts | askii edit --wiki-path ./docs --use-wiki "add connection pooling"
askii do --wiki-path ./docs --use-wiki "implement the auth flow described in the docs"

PowerShell

askii ask --wiki-path .\docs --use-wiki "how do I configure the database?"
Get-Content src\db.ts | askii edit --wiki-path .\docs --use-wiki "add connection pooling"
askii do --wiki-path .\docs --use-wiki "implement the auth flow described in the docs"

commit — Generate a commit message

Reads the staged diff (or, if nothing is staged, the working-tree diff) plus the list of changed files, asks the LLM to write a well-formed Git commit message, and prints it to stdout. Pipe-friendly — use it with git commit:

bash

git commit -m "$(askii commit)"
askii commit --dir ./my-project

PowerShell

git commit -m "$(askii commit)"
askii commit --dir ..\my-project

The diff is capped at 12,000 characters to keep context tight. The output is cleaned of markdown fences, quotes, and Commit message: labels, so it's ready to pass straight to git commit -m.

note — Notes / tasks / reminders

Type free text and the AI auto-classifies it into a note, task (with low / medium / high priority), or reminder (with a due time). Entries are stored globally at ~/.askii/notes.json, tagged by workspace, and full-text searchable everywhere.

bash

askii note add "the API rate limit is 100 req/min"
askii note add "task: fix the login bug, high priority"
askii note add "remind me to check the build in 30 minutes"
askii note add --shot "remember this screen state"   # attach a full-screen screenshot
askii note list                                       # list all entries (most-recent first)
askii note list "login"                               # filter by full-text query
askii note search "login"                             # full-text search
askii note done abc12345                              # toggle a task's done state
askii note delete abc12345                            # delete an entry
askii note due                                        # list reminders that are due now

PowerShell

askii note add "the API rate limit is 100 req/min"
askii note add "task: fix the login bug, high priority"
askii note add "remind me to check the build in 30 minutes"
askii note add --shot "remember this screen state"
askii note list
askii note search "login"
askii note done abc12345
askii note delete abc12345
askii note due

Subcommands:

| Subcommand | Description | | --------------------- | -------------------------------------------------- | | add "<text>" | Add a note / task / reminder (AI auto-classifies) | | add --shot "<text>" | Attach a full-screen screenshot to the entry | | list [query] | List all entries, or filter by full-text query | | search "<query>" | Full-text search across all entries | | done <id> | Toggle a task's done state | | delete <id> | Delete an entry | | due | List reminders that are due now (marks them fired) |

Reminders: the CLI has no background scheduler, so reminders don't fire automatically. Run askii note due to see what's overdue — it prints the due entries and marks them fired. In the interactive REPL, /note add will ask a clarifying question if the reminder time is ambiguous.

browse — Browser agent

Launches a Puppeteer browser, takes a screenshot of the current page and its URL, sends both to the AI, and executes the returned action. Repeats until the AI returns DONE or --max-rounds is reached. Requires a vision-capable model (e.g. llava, moondream2).

By default the browser window is visible. Pass --headless to run in the background.

Requires Chrome or Chromium to be installed. Use --chrome-path (or ASKII_CHROME_PATH) to specify the executable path if it is not detected automatically.

bash

askii browse --ollama-model llava "go to https://example.com and click Learn more"
askii browse --yes --ollama-model llava "search Google for Node.js and open the first result"
askii browse --headless --yes --ollama-model llava "check the title of https://github.com"
askii browse --max-rounds 10 --ollama-model llava "fill in the login form on example.com"
askii browse -p lmstudio --lmstudio-model llava-1.5 "go to news.ycombinator.com"
askii browse --chrome-path "/usr/bin/chromium" --ollama-model llava "go to example.com"

PowerShell

askii browse --ollama-model llava "go to https://example.com and click Learn more"
askii browse --yes --ollama-model llava "search Google for Node.js and open the first result"
askii browse --headless --yes --ollama-model llava "check the title of https://github.com"
askii browse --max-rounds 10 --ollama-model llava "fill in the login form on example.com"
askii browse -p lmstudio --lmstudio-model llava-1.5 "go to news.ycombinator.com"
askii browse --chrome-path "C:\Program Files\Google\Chrome\Application\chrome.exe" --ollama-model llava "go to example.com"

Each round the AI can return one of:

• goto — navigate to a URL
• click — click an element by CSS selector
• type — type text into an element by CSS selector (clears existing value first)
• wait_for — wait until a CSS selector appears in the DOM
• back — navigate back in browser history
• forward — navigate forward in browser history
• DONE — task complete, stop the loop

Without --yes, each proposed action is shown with its reasoning and requires y confirmation before executing.

Options

| Flag | Short | Description | Default | | -------------------- | ----- | ------------------------------------------------------------------------------------- | ------------------------------- | | --platform | -p | LLM platform: ollama, lmstudio, openai, anthropic, opencodego, askiicloud | ollama | | --ollama-url | | Ollama server URL | http://localhost:11434 | | --lmstudio-url | | LM Studio server URL | ws://localhost:1234 | | --ollama-model | | Ollama model | gemma4:e4b | | --lmstudio-model | | LM Studio model | qwen/qwen3-coder-30b | | --openai-key | | OpenAI API key (env: ASKII_OPENAI_KEY) | | | --openai-model | | OpenAI model | gpt-5-mini | | --openai-url | | OpenAI-compatible base URL (env: ASKII_OPENAI_URL) | | | --anthropic-key | | Anthropic API key (env: ASKII_ANTHROPIC_KEY) | | | --anthropic-model | | Anthropic model (env: ASKII_ANTHROPIC_MODEL) | claude-sonnet-4-6 | | --opencodego-key | | opencode Go API key (env: ASKII_OPENCODEGO_KEY) | | | --opencodego-model | | opencode Go model (env: ASKII_OPENCODEGO_MODEL) | glm-5.2 | | --opencodego-url | | opencode Go base URL (env: ASKII_OPENCODEGO_URL) | https://opencode.ai/zen/go/v1 | | --askiicloud-key | | ASKII Cloud API key (env: ASKII_CLOUD_KEY) | | | --askiicloud-model | | ASKII Cloud model (env: ASKII_CLOUD_MODEL) | askii-default | | --mode | | Response style: helpful, funny | funny | | --max-rounds | | Max agent rounds for do / generate / control / browse | 5 | | --dir | | Working directory for do / generate | cwd | | --code | -c | Code input (alternative to stdin) | | | --file | | Filename of the code (e.g. src/utils.ts) — also context file for generate | | | --instruction | -i | Extra instruction for generate | | | --yes | -y | Auto-confirm all actions | | | --headless | | Run Puppeteer headlessly for browse | false (visible) | | --chrome-path | | Path to Chrome/Chromium executable for browse | | | --wiki-path | | Path to folder with .md docs for wiki RAG (env: ASKII_WIKI_PATH) | | | --use-wiki | | Inject wiki context into ask / edit / do (env: ASKII_USE_WIKI=1) | |

Environment Variables

bash

export ASKII_PLATFORM=ollama

# Ollama
export ASKII_OLLAMA_URL=http://localhost:11434
export ASKII_OLLAMA_MODEL=gemma4:e4b

# LM Studio
export ASKII_LMSTUDIO_URL=ws://localhost:1234
export ASKII_LMSTUDIO_MODEL=qwen/qwen3-coder-30b

# OpenAI
export ASKII_OPENAI_KEY=sk-...
export ASKII_OPENAI_MODEL=gpt-5-mini
export ASKII_OPENAI_URL=   # leave empty for api.openai.com

# Anthropic
export ASKII_ANTHROPIC_KEY=sk-ant-...
export ASKII_ANTHROPIC_MODEL=claude-sonnet-4-6

# opencode Go
export ASKII_OPENCODEGO_KEY=...
export ASKII_OPENCODEGO_MODEL=glm-5.2
export ASKII_OPENCODEGO_URL=https://opencode.ai/zen/go/v1

# ASKII Cloud
export ASKII_CLOUD_KEY=...
export ASKII_CLOUD_MODEL=askii-default

# Shared
export ASKII_MODE=funny
export ASKII_MAX_ROUNDS=5
export ASKII_CHROME_PATH=/usr/bin/chromium

# Docs wiki RAG
export ASKII_WIKI_PATH=./docs
export ASKII_USE_WIKI=1

PowerShell

$env:ASKII_PLATFORM = "ollama"

# Ollama
$env:ASKII_OLLAMA_URL = "http://localhost:11434"
$env:ASKII_OLLAMA_MODEL = "gemma4:e4b"

# LM Studio
$env:ASKII_LMSTUDIO_URL = "ws://localhost:1234"
$env:ASKII_LMSTUDIO_MODEL = "qwen/qwen3-coder-30b"

# OpenAI
$env:ASKII_OPENAI_KEY = "sk-..."
$env:ASKII_OPENAI_MODEL = "gpt-5-mini"
$env:ASKII_OPENAI_URL = ""   # leave empty for api.openai.com

# Anthropic
$env:ASKII_ANTHROPIC_KEY = "sk-ant-..."
$env:ASKII_ANTHROPIC_MODEL = "claude-sonnet-4-6"

# opencode Go
$env:ASKII_OPENCODEGO_KEY = "..."
$env:ASKII_OPENCODEGO_MODEL = "glm-5.2"
$env:ASKII_OPENCODEGO_URL = "https://opencode.ai/zen/go/v1"

# ASKII Cloud
$env:ASKII_CLOUD_KEY = "..."
$env:ASKII_CLOUD_MODEL = "askii-default"

# Shared
$env:ASKII_MODE = "funny"
$env:ASKII_MAX_ROUNDS = "5"
$env:ASKII_CHROME_PATH = "C:\Program Files\Google\Chrome\Application\chrome.exe"

# Docs wiki RAG
$env:ASKII_WIKI_PATH = ".\docs"
$env:ASKII_USE_WIKI = "1"

Platforms

Ollama (default)

bash

ollama pull gemma4:e4b
askii ask "what is a closure?"

PowerShell

ollama pull gemma4:e4b
askii ask "what is a closure?"

LM Studio

bash

# Start LM Studio with local server enabled
askii -p lmstudio ask "explain this function"
askii -p lmstudio --lmstudio-model "my-model" ask "explain this function"

PowerShell

# Start LM Studio with local server enabled
askii -p lmstudio ask "explain this function"
askii -p lmstudio --lmstudio-model "my-model" ask "explain this function"

OpenAI

bash

askii -p openai --openai-key sk-... ask "what does this do?"
askii -p openai --openai-key sk-... --openai-model gpt-4-turbo do "add error handling"
# Azure OpenAI or any compatible API:
askii -p openai --openai-key sk-... --openai-url https://my-resource.openai.azure.com ask "explain"

PowerShell

askii -p openai --openai-key sk-... ask "what does this do?"
askii -p openai --openai-key sk-... --openai-model gpt-4-turbo do "add error handling"
# Azure OpenAI or any compatible API:
askii -p openai --openai-key sk-... --openai-url https://my-resource.openai.azure.com ask "explain"

Anthropic

bash

askii -p anthropic --anthropic-key sk-ant-... ask "what does this do?"
askii -p anthropic --anthropic-key sk-ant-... --anthropic-model claude-sonnet-4-6 do "add error handling"
askii -p anthropic --anthropic-key sk-ant-... --anthropic-model claude-haiku-4-5 explain "arr.reduce((a, b) => a + b, 0)"

PowerShell

askii -p anthropic --anthropic-key sk-ant-... ask "what does this do?"
askii -p anthropic --anthropic-key sk-ant-... --anthropic-model claude-sonnet-4-6 do "add error handling"
askii -p anthropic --anthropic-key sk-ant-... --anthropic-model claude-haiku-4-5 explain "arr.reduce((a, b) => a + b, 0)"

opencode Go

A hosted, multi-model coding subscription (opencode.ai/go). Most models use an OpenAI-compatible endpoint; Qwen and MiniMax models use an Anthropic-compatible one — ASKII routes automatically based on the model id. See the full model list at opencode.ai/zen/go/v1/models.

bash

askii -p opencodego --opencodego-key ... ask "what does this do?"
askii -p opencodego --opencodego-key ... --opencodego-model kimi-k2.7-code do "add error handling"
askii -p opencodego --opencodego-key ... --opencodego-model qwen3.7-max explain "arr.reduce((a, b) => a + b, 0)"

PowerShell

askii -p opencodego --opencodego-key ... ask "what does this do?"
askii -p opencodego --opencodego-key ... --opencodego-model kimi-k2.7-code do "add error handling"
askii -p opencodego --opencodego-key ... --opencodego-model qwen3.7-max explain "arr.reduce((a, b) => a + b, 0)"

ASKII Cloud

An in-house, OpenAI-compatible inference service (api.askii.dev). All it needs is an API key — the base URL is fixed to https://api.askii.dev/v1.

bash

askii -p askiicloud --askiicloud-key ... ask "what does this do?"
askii -p askiicloud --askiicloud-key ... --askiicloud-model askii-default do "add error handling"
askii -p askiicloud --askiicloud-key ... explain "arr.reduce((a, b) => a + b, 0)"

PowerShell

askii -p askiicloud --askiicloud-key ... ask "what does this do?"
askii -p askiicloud --askiicloud-key ... --askiicloud-model askii-default do "add error handling"
askii -p askiicloud --askiicloud-key ... explain "arr.reduce((a, b) => a + b, 0)"